Best practices for conceptual modelling in environmental planning and management

Conceptual modelling is used in many fields with a varying degree of formality. In environmental applications, conceptual models are used to express relationships, explore and test ideas, check inference and causality, identify knowledge and data gaps, synchronize mental models and build consensus, and to highlight key or dominant processes. Due to their sometimes apparent simplicity, development and use of a conceptual model is often an attractive option when tackling an environmental problem situation. However, we have experienced many examples where conceptual modelling has failed to effectively assist in the resolution of environmental problems. This paper explores development and application of conceptual modelling to environmental problems, and identifies a range of best practices for environmental scientists and managers that include considerations of stakeholder participation and trust, model development and representation, integration of different and disparate conceptual models, model maturation, testing, and transition to application within the problem situation.     

CHEOPS: A tool-integration platform for chemical process modelling and simulation

A large number of modelling tools exist for the construction and solution of mathematical models of chemical processes. Each (chemical) process modelling tool provides its own model representation and model definition functions as well as its own solution algorithms, which are used for performing computer-aided studies for the process under consideration. However, in order to support reusability of existing models and to allow for the combined use of different modelling tools for the study of complex processes, model integration is needed. This paper presents a concept for an integration platform that allows for the integration of modelling tools, combining their models to build up a process model and performing computer-aided studies based on this integrated process model. In order to illustrate the concept without getting into complicated algorithmic issues, we focus on steady-state simulation using models comprising only algebraic equations. The concept is realized in the component-based integration platform CHEOPS, which focuses on integrating and solving existing models rather than providing its own modelling capabilities.     

Integrated assessment and modelling: Overview and synthesis of salient dimensions

Integrated assessment and its inherent platform, integrated modelling, present an opportunity to synthesize diverse knowledge, data, methods and perspectives into an overarching framework to address complex environmental problems. However to be successful for assessment or decision making purposes, all salient dimensions of integrated modelling must be addressed with respect to its purpose and context. The key dimensions include: issues of concern; management options and governance arrangements; stakeholders; natural systems; human systems; spatial scales; temporal scales; disciplines; methods, models, tools and data; and sources and types of uncertainty. This paper aims to shed light on these ten dimensions, and how integration of the dimensions fits in the four main phases in the integrated assessment process: scoping, problem framing and formulation, assessing options, and communicating findings. We provide examples of participatory processes and modelling tools that can be used to achieve integration.     

Seeing the forest through the trees: A review of integrated environmental modelling tools

Today’s interconnected socio-economic and environmental challenges require the combination and reuse of existing integrated modelling solutions. This paper contributes to this overall research area, by reviewing a wide range of currently available frameworks, systems and emerging technologies for integrated modelling in the environmental sciences. Based on a systematic review of the literature, we group related studies and papers into viewpoints and elaborate on shared and diverging characteristics. Our analysis shows that component-based modelling frameworks and scientific workflow systems have been traditionally used for solving technical integration challenges, but ultimately, the appropriate framework or system strongly depends on the particular environmental phenomenon under investigation. The study also shows that – in general – individual integrated modelling solutions do not benefit from components and models that are provided by others. It is this island (or silo) situation, which results in low levels of model reuse for multi-disciplinary settings. This seems mainly due to the fact that the field as such is highly complex and diverse. A unique integrated modelling solution, which is capable of dealing with any environmental scenario, seems to be unaffordable because of the great variety of data formats, models, environmental phenomena, stakeholder networks, user perspectives and social aspects. Nevertheless, we conclude that the combination of modelling tools, which address complementary viewpoints – such as service-based combined with scientific workflow systems, or resource-modelling on top of virtual research environments – could lead to sustainable information systems, which would advance model sharing, reuse and integration. Next steps for improving this form of multi-disciplinary interoperability are sketched.     

CROSPAL,software that uses agronomic expert knowledge to assist modules selection for crop growth simulation

Crop growth models are used for a wide range of objectives. For each objective a specific model has to be developed, because the reusability of a model is often limited by the necessity of a fundamental restructuring to adapt it to a different objective. To overcome this limitation, we developed a method to facilitate model restructuring by a novel combination of software technology with expert knowledge.This resulted in the decision-making software application CROSPAL (CROp Simulator: Picking and Assembling Libraries). CROSPAL includes (1) a library of processes each containing different modelling approaches for each crop physiological process and (2) a procedure based on expert knowledge of how to combine the different processes for the objective of the simulation.A brief overview of the state of the art in crop modelling is presented, followed by an account of the developed concept to improve flexibility in crop modelling considering expert knowledge. We describe the design of the software and how expert knowledge is integrated. The use of CROSPAL is illustrated for the modelling of crop phenology. We conclude that CROSPAL is a helpful tool to improve flexibility in crop modelling considering expert knowledge but further development and evaluation is required to extend its range of application to more processes and issues crop modelling is presently addressing.     

CITY DRAIN © – An open source approach for simulation of integrated urban drainage systems

In the last years design procedures of urban drainage systems have shifted from end of pipe design criteria to ambient water quality approaches requiring integrated models of the system for evaluation of measures. Emphasis is put on the improvement of the receiving water quality and the overall management of river basins, which is a core element of the Water Framework Directive (WFD) as well.Typically, it is not necessary to model the whole variety of effects on the receiving water but to focus on the few dominating ones. Only pollutants and processes that have a direct and significant influence on the selected impacts need to be described quantitatively, whereas all other processes can be neglected. Hence, pragmatism is required to avoid unnecessary complexity of integrated models. This is as well true for software being used in daily engineering work, requiring simplicity in handling and a certain flexibility to be adjusted for different scenarios.CITY DRAIN © was developed to serve these needs. Therefore it was developed in the Matlab/Simulink © environment, enabling a block wise modelling of the different parts of the urban drainage system (catchment, sewer system, storage devises, receiving water, etc.). Each block represents a system element (subsystem) with different underlying modelling approaches for hydraulics and mass transport. The different subsystems can be freely arranged and connected to each other in order to describe an integrated urban drainage system. The open structure of the software allows to add own blocks and/or modify blocks (and underlying models) according to the specific needs.The application of CITY DRAIN is shown within the integrated modelling case study Vils/Reutte. Further additional applications for CITY DRAIN, including batch simulations, real time control (RTC) and model based predictive control (MBPC) are presented and discussed.     

Evolution of mathematical models of chaotic systems based on multiobjective genetic programming

This work is concerned with the identification of models for nonlinear dynamical systems using multiobjective evolutionary algorithms. Systems modelling involves the processes of structure selection, parameter estimation, model performance and model validation and involves a complex solution space. Evolutionary Algorithms (EAs) are search and optimisation tools founded on the principles of natural evolution and genetics, which are suitable for a wide range of application areas. Due to the versatility of these tools and motivated by the versatility of genetic programming (GP), this evolutionary paradigm is proposed for this modelling problem. GP is then combined with a multiobjective function definition scheme. Multiobjective genetic programming (MOGP) is applied to multiple, conflicting objectives and yields a set of candidate parsimonious and valid models, which reproduce the original system behaviour. The MOGP approach is then demonstrated as being applicable for system modelling with chaotic dynamics. The circuit introduced by Chua, being one of the most popular benchmarks for studying nonlinear oscillations, and the Duffing–Holmes oscillator are the systems to test the evolutionary-based modelling approach introduced in this paper.     

Selecting among five common modelling approaches for integrated environmental assessment and management

The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings.     

Integrating a formal method into a software engineering process with UML and Java

We describe how CSP-OZ, a formal method combining the process algebra CSP with the specification language Object-Z, can be integrated into an object-oriented software engineering process employing the UML as a modelling and Java as an implementation language. The benefit of this integration lies in the rigour of the formal method, which improves the precision of the constructed models and opens up the possibility of (1) verifying properties of models in the early design phases, and (2) checking adherence of implementations to models. The envisaged application area of our approach is the design of distributed reactive systems. To this end, we propose a specific UML profile for reactive systems. The profile contains facilities for modelling components, their interfaces and interconnections via synchronous/broadcast communication, and the overall architecture of a system. The integration with the formal method proceeds by generating a significant part of the CSP-OZ specification from the initially developed UML model. The formal specification is on the one hand the starting point for verifying properties of the model, for instance by using the FDR model checker. On the other hand, it is the basis for generating contracts for the final implementation. Contracts are written in the Java Modeling Language (JML) complemented by CSP_jassda, an assertion language for specifying orderings between method invocations. A set of tools for runtime checking can be used to supervise the adherence of the final Java implementation to the generated contracts. This research was partially supported by the DFG project ForMooS (grants OL 98/3-2 and WE 2290/5-1). C. B. Jones     

Model decomposition and reduction tools for large-scale networks in systems biology

Biological system models are routinely developed in modern systems biology research following appropriate modelling/experiment design cycles. Frequently these take the form of high-dimensional nonlinear Ordinary Differential Equations that integrate information from several sources; they usually contain multiple time-scales making them difficult even to simulate. These features make systems analysis (understanding of robust functionality) — or redesign (proposing modifications in order to improve or modify existing functionality) a particularly hard problem. In this paper we use concepts from systems theory to develop two complementary tools that can help us understand the complex behaviour of such system models: one based on model decomposition and one on model reduction. Our aim is to algorithmically produce biologically meaningful, simplified models, which can then be used for further analysis and design. The tools presented are applied on a model of the Epidermal Growth Factor signalling pathway.     

Modelling of spatial point processes derived from a sequence of auto-Poisson lattice schemes

Spatial point processes form a set of statistical tools capable of modelling many environmental processes. They can deal with spatial interactions and dependencies between individuals which is an essential framework in environmental modelling. In this context, we focus on inhibitory pairwise interaction point processes that can be obtained as the limit of a suitable sequence of auto-Poisson lattice schemes. We review the limit theorems concerned, present a computer software (SPPA) and analyze the results of a Monte Carlo simulation study based on a particular pairwise interaction model.     

Improving ecosystem services modelling: Insights from a Bayesian network tools review

Numerous studies attempt to unravel the role played by Biodiversity in ecosystems and ES reliance on Biodiversity. Achieving this aim is difficult given: the multi-layered Biodiversity-ES relationship; the temporal and spatial heterogeneity of ES; and, the interactions between biotic and abiotic components in ecosystems influencing processes and services. Bayesian networks have recently gained importance in ecological modelling. The integration of empirical data with expert knowledge and the explicit treatment of uncertainties, demonstrate their usefulness. Publications describing network-based Biodiversity-ES models, demonstrate their application is still limited. A watershed's environmental risk management network modelled from a Biodiversity-ES perspective is discussed. It demonstrates an improvement on conventional approaches, expressing risk in terms of the underlying causal relations between environmental risk events, triggers, controls and consequences. The model is developed in AgenaRisk and two other tools, Netica and Hugin. A comparison between them highlights the dependence on the tool of choice.     

A requirements engineering environment within a tightly integrated SDE

This paper describes the outside functionality of an RE environment within an integrated software development environment. Furthermore, an integrator tool for the transition to software system architecture modelling is presented. The tools discussed are editors, analysers, executors, monitors, and integration tools of different characteristics for horizontal integration (within RE) and vertical integration (to architecture modelling). All tools are tightly integrated and work incrementally, therefore allowing different forms of construction and modification processes and giving substantial support.     

Regime shifts in coupled socio-environmental systems: Review of modelling challenges and approaches

Increasing attention to regime shifts, critical transitions, non-marginal changes, and systemic shocks calls for the development of models that are able to reproduce or grow structural changes that occur over time periods perceived as abrupt. This paper highlights specific modelling challenges to consider when exploring coupled socio-environmental systems experiencing regime shifts. We explore these challenges in the context of four modelling approaches that have been applied to the study of regime shifts in coupled socio-environmental systems: statistical, system dynamics, equilibrium and agent-based modelling. When reviewing these modelling approaches we reflect on a set of criteria including the ability of an approach (1) to capture feedbacks between social and environmental system, (2) to represent the sources of regime shifts, (3) to incorporate complexity aspects, and (4) to deal with regime shift identification. Many of the modelling examples considered do not provide information on all these criteria, which receive a lot of attention in empirical studies of registered regime shifts. This suggests a need to develop a common modelling terminology in the domain of modelling for resilience and regime shifts. When discussing strengths and weaknesses of various modelling paradigms we conclude that a hybrid approach is likely to provide most insights into the processes and consequences of regime shifts. Challenges and frontier directions of research for designing models to study regime shifts in coupled socio-environmental systems are outlined.     

“It was an artefact not the result”: A note on systems dynamic model development tools

Environmental modelling is done more and more by practising ecologists rather than computer scientists or mathematicians. This is because there is a broad spectrum of development tools available that allows graphical coding of complex models of dynamic systems and help to abstract from the mathematical issues of the modelled system and the related numerical problems for estimating solutions. In this contribution, we study how different modelling tools treat a test system, a highly non-linear predator–prey model, and how the numerical solutions vary. We can show that solutions (a) differ if different development tools are chosen but the same numerical procedure is selected; (b) depend on undocumented implementation details; (c) vary even for the same tool but for different versions; and (d) are generated but with no notifications on numerical problems even if these could be identified. We conclude that improved documentation of numeric methods used in the modelling software is essential to make sure that process based models formulated in terms of these modelling packages do not become “black box” models due to uncertainty in integration methods.